Analytical Framework Research Articles

Understanding society: a reflexive foresight matrix for navigating complexity and shaping the future

Purpose This paper introduces the foresight matrix, a conceptual framework for foresight analysis rooted in critical realism (CR) and complexity theory. It aims to address the need for a comprehensive theoretical perspective that embraces emergence and recognizes the interplay between different layers of reality. Informed by critical theory within futures studies, the study seeks to provide additional foresight theoretical perspectives in addressing contemporary societal challenges and collectively shaping desirable futures. Design/methodology/approach The proposed reflexive foresight matrix incorporates elements of CR, complexity theory and morphogenesis theory, providing an alternative conceptual framework for analyzing complex social challenges. It integrates the vertical layers – empirical, actual and real – and horizontal dimensions – structure, agency and culture. This matrix guides researchers through a systematic analysis of structural barriers, cultural influences and individual agency, offering a comprehensive tool for understanding the underlying mechanisms driving social change. Findings The reflexive foresight matrix dissects complex situations into structure, agency and culture dimensions, enabling a thorough understanding of societal dynamics by examining the interplay between these dimensions and their influence on individual and collective behaviors. This conceptual framework guides researchers through a systematic analysis of structural barriers, cultural influences and individual agency, uncovering the mechanisms driving social change. Through reflexive monitoring and temporal action analysis, it explores historical and contextual factors, informing future tendencies. Practical implications The reflexive foresight matrix provides a multidimensional lens for understanding social issues, prompting researchers to consider the interplay between structure, agency and culture across different layers of reality. By exploring historical and contextual factors, this framework enables an insight into diverse perspectives and their impact on future outlooks. Furthermore, the matrix facilitates critical inquiry into prevailing power dynamics and narratives, offering insights into societal injustices and inequalities. This critical examination empowers stakeholders to challenge dominant narratives and work toward more equitable and desirable futures. Social implications The proposed reflexive foresight matrix offers a comprehensive approach to analyzing complex social challenges, potentially impacting futures thinking and foresight practices. By integrating CR, complexity theory and morphogenesis theory, the framework fosters a deep understanding of the interplay between various factors influencing future tendencies. This comprehensive view of problems allows analysts to consider structural barriers, cultural influences and agency, thereby enhancing foresight efforts in addressing contemporary challenges. Originality/value The proposed reflexive foresight matrix contributes to futures thinking and foresight practices by offering a comprehensive approach to analyzing complex social challenges. By combining CR, complexity theory and morphogenesis theory, the framework fosters an insightful understanding of the interplay between various factors influencing future trajectories. Moreover, the integration of critical perspectives and reflexive methodologies into foresight practices underscores the importance of challenging dominant narratives, fostering inclusive decision-making processes and empowering individuals and communities to shape their futures.

“Planetary phase shift” as a new systems framework to navigate the evolutionary transformation of human civilisation

Purpose The paper aims to address a gap in foresight study and practice relating to the lack of unifying theoretical systems frameworks capable of examining empirical data from across a wide range of different ecological, social, political and economic systems. It attempts to develop a new “collective forward intelligence” that can not only make sense of these disparate trends and processes as symptoms of a wider planetary system but also, on this basis, construct accurate and plausible future scenarios to underpin national and international decision-making. Design/methodology/approach This study conducts a transdisciplinary integration of C. S. Holling’s adaptive cycle with phase-transition phenomena across biology, physics and chemistry, applied on societal and civilisational scales. A systems methodology is then applied to integrate historical and empirical data across the energy, food, transport, materials and information sectors of civilisation’s production system. Findings The paper develops planetary phase shift theory as a new collective forward intelligence framework for foresight study and practice, formalising the notion that humanity has arrived at an unprecedented historic and geological turning point. It finds that multiple global crises across both earth and human systems are symptoms of the last stages of the life-cycle of global industrialisation civilisation, which is the potential precursor either for collapse, or for a new civilisational life-cycle that may represent a new stage in the biological and cultural evolution of the human species. Research limitations/implications The research sets out a new empirically grounded theoretical framework for complex scenario analysis. This can develop more robust approaches to foresight study and practice, scenario development and forecasting. It suggests the need for a new research programme to understand the dynamics of the planetary phase shift and its diverse implications for societies, industry, technology and politics. The research is limited in that the current paper does not explore how it can be applied in this way. It identifies broad scenarios for a post-industrial civilisational life-cycle but does not identify the variety of complex subsets of these. Practical implications The paper provides powerful practical implications to develop new methodology based on planetary phase shift theory for strategic planning, risk assessment and management, as well as public policy and decision-making. Social implications The paper suggests the urgency and necessity of bold and radical societal transformation and implies key areas for civil society to focus on in innovating new values, worldviews and operating systems with a focus on the next life-cycle. Originality/value To the best of the author’s knowledge, this paper provides the first integrated transdisciplinary theoretical and empirical framework to understand how the interplay of earth system crises, societal change and technology disruptions is driving large-scale civilisational transformation with complex local ramifications.

Profiling of 24-nt phasiRNAs in Rice Anther by Massively Parallel Sequencing and Stem-Loop Reverse Transcription PCR.

Small RNAs are highly abundant and play important roles in plant reproduction. Profiling of small RNAs in reproductive tissues is a critical step in understanding their biology. Here, we describe a protocol for small RNA profiling in rice anthers, with a focus on an abundantly expressed but little-understood reproductive small RNA class named 24-nucleotide phased secondary small interfering RNAs (24-nt phasiRNAs). The protocol details small RNA library preparation steps for high-throughput sequencing, with a subsequent bioinformatic analysis framework. A low-throughput stem-loop reverse transcription PCR protocol for quick semi-quantification of small RNAs is also included as a complementary approach. The collective protocol, although focused on 24-nt phasiRNAs, should be amenable to other small RNA classes in various plant reproductive tissues.

Digitally Driven Urban Governance: Framework and Evaluation in China

With the rapid development of digital technology, the role of digitalisation in urban governance continues to emerge. Building a theoretical analysis framework and evaluation system of digitally driven urban governance has important theoretical and practical significance for stimulating the efficiency of digital technology tools and improving the energy level of urban digital governance. This paper aims to explore the mechanism of urban governance enabled by digital technology, innovatively change the previous thinking mode that only attaches importance to facility construction and e-government platforms, adopt ecological thinking, and comprehensively consider the role of “soft elements” such as strategic support, industrial support, the security environment, talent support, and the market environment. Then, the extreme value variance method and the coefficient of variation method are used to calculate the overall capacity and secondary index scores of each city, and the standard deviation of secondary index scores is used to represent the sub-environmental balance of the cross-sectional data of China’s provinces. In order to further explore which indicators restrict the improvement of China’s urban digital governance capacity, this study also constructs an obstacle degree model. The results show the following: (1) The overall capability of China’s digitally driven urban governance is low, with a total score of 27.25, indicating that China’s digitally driven urban governance is in its infancy. (2) There is a significant development imbalance among Chinese provinces, with Beijing ranking first with a score of 81.16, and Tibet, Qinghai, Xinjiang, Heilongjiang, and Ningxia scoring less than 13.30 points, ranking as the bottom 5 among the 31 provinces. (3) The shortcomings of talent support, industrial support, and the security environment restrict the improvement of the entire digital ecological governance ability.

Liability regulation on short video platforms: balancing freedom of expression and copyright protection

Abstract The rise of short video platforms has fundamentally altered the balance between freedom of expression and copyright protection, challenging traditional legal frameworks like the Safe Harbor Principle. This paper critically examines the evolving legal landscape, with particular focus on the implications of Article 17 of the EU’s Copyright Directive in the Digital Single Market (DSM Directive), especially for small platforms, creators, and users. Through comparative analysis of international legal frameworks and case studies, the study delves into the challenges faced by stakeholders in navigating platform liability, algorithmic content moderation, and user rights. The research highlights how the existing legal environment, while aiming to protect copyright holders, often disproportionately favors large platforms, undermining the expressive freedoms and fair use rights of smaller creators and users. Furthermore, the paper addresses the role of remix culture on short video platforms, discussing how transformative works and user-generated content foster cultural diversity and innovation. It advocates for reforms that balance copyright enforcement with freedom of expression, promoting cooperative licensing models, nuanced content moderation, and expanded fair use exemptions to support a more equitable digital ecosystem where creativity, access, and protection coexist effectively.

The politicization of education policies: The case of Ghana’s Free Senior High School Policy

While many scholars recognize and criticize the politicization of education policies, scholarly attention to the strategies politicians utilize to politicize educational policy discourses remains limited. Focusing on the officials of Ghana’s two major political parties, the New Patriotic Party (NPP) and the National Democratic Congress (NDC), as policy actors, this paper investigates how officials of these two parties operationalized discussions regarding Ghana’s Free Senior High School Policy (FSHSP) to garner support for their parties while stoking resentment for their political opponents. The study employs a critical discourse analysis (CDA) framework and a dataset of 175 documents, including news stories, press releases, party manifestos, and government publications. The analysis reveals that both parties resorted to strategies of positive self-presentation and negative other presentation. The NPP contrasted its regime with the NDC’s tenure and framed the NDC as a threat to FSHSP and the education of the poor and vulnerable. The NDC problematized and highlighted implementation bottlenecks while framing the NPP and FSHSP as threats to quality education. I argue that through these strategies, NPP officials aimed to maintain incumbency while NDC officials advocated a regime change. The paper concludes by emphasizing the potential risks associated with politicizing education policies.

Research on Adhesion Pull-Off Behavior of Rigid Flat Punch and Viscoelastic Substrate

Interfacial adhesion is one of the key factors affecting the reliability of micro–nano systems. The adhesion contact mechanism is still unclear as the time-dependent viscoelasticity of soft materials. To clarify the adhesion interaction, the pull-off detachment between the rigid flat punch and viscoelastic substrate is explored considering the viscoelasticity of soft materials and rate-dependent adhesion. Taking the Lennard-Jones (L-J) potential characterizing interfacial adhesion and the Prony series defining the viscoelasticity of materials as references, the bilinear cohesion zone model (CZM) and standard Maxwell model are employed, and an adhesion analysis framework is established by combining finite element technology. The influence laws of the loading and unloading rates, material relaxation coefficients and size effect on adhesion pull-off behavior are revealed. The results show that the pull-off force is independent of the material relaxation effect and related to the unloading rate. When v^ ≥ 50 or v^ < 0.01, the pull-off force has nothing to do with the unloading rate, but when 0.01 < v^ < 50, the pull-off force increases with the increasing unloading rate. Also, it is controlled by the size effect, and the changing trend conforms to the MD-n model proposed by Jiang. The energy required for interfacial separation (i.e., effective adhesion work) is a result of the comprehensive influence of unloading rates, material properties and the relaxation effect, which is consistent with Papangelo1’s research results. In addition, we derive the critical contact radius of the transition from the Kendall solution to the strength control solution. This work not only provides a detailed solution for the interfacial adhesion behavior but also provides guidance for the application of adhesion in Micro-Electro-Mechanical Systems (MEMSs).

When Automated Assessment Meets Automated Content Generation: Examining Text Quality in the Era of GPTs

The use of machine learning (ML) models to assess and score textual data has become increasingly pervasive in an array of contexts including natural language processing, information retrieval, search and recommendation, and credibility assessment of online content. A significant disruption at the intersection of ML and text are text-generating large-language models (LLMs) such as generative pre-trained transformers (GPTs). We empirically assess the differences in how ML-based scoring models trained on human content assess the quality of content generated by humans versus GPTs. To do so, we propose an analysis framework that encompasses essay scoring ML-models, human and ML-generated essays, and a statistical model that parsimoniously considers the impact of type of respondent, prompt genre, and the ML model used for assessment model. A rich testbed is utilized that encompasses 18,460 human-generated and GPT-based essays. Results of our benchmark analysis reveal that LLMs and transformer pretrained language models (PLMs) more accurately score human essay quality as compared to CNN/RNN and feature-based ML methods. Interestingly, we find that LLMs and transformer PLMs tend to score GPT-generated text 10-20% higher on average, relative to human-authored documents. Conversely, traditional deep learning and feature-based ML models score human text considerably higher. Further analysis reveals that even though the LLMs and transformer PLMs are exclusively fine-tuned on human text, they more prominently attend to certain tokens appearing only in GPT-generated text, possibly (in part) due to familiarity/overlap in pre-training. Our framework and results have implications for text classification settings where automated scoring of text is likely to be disrupted by generative AI.

Integrating LLMs and software-defined resources for enhanced demonstrative cloud computing education in university curricula

This paper explores the integration of Large Language Models (LLMs) and Software-Defined Resources (SDR) as innovative tools for enhancing cloud computing education in university curricula. The study emphasizes the importance of practical knowledge in cloud technologies such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), DevOps, and cloud-native environments. It introduces Lean principles to optimize the teaching framework, promoting efficiency and effectiveness in learning. By examining a comprehensive educational reform project, the research demonstrates that incorporating SDR and LLMs can significantly enhance student engagement and learning outcomes, while also providing essential hands-on skills required in today’s dynamic cloud computing landscape. A key innovation of this study is the development and application of the Entropy-Based Diversity Efficiency Analysis (EDEA) framework, a novel method to measure and optimize the diversity and efficiency of educational content. The EDEA analysis yielded surprising results, showing that applying SDR (i.e., using cloud technologies) and LLMs can each improve a course’s Diversity Efficiency Index (DEI) by approximately one-fifth. The integrated approach presented in this paper provides a structured tool for continuous improvement in education and demonstrates the potential for modernizing educational strategies to better align with the evolving needs of the cloud computing industry.

Using normalisation process theory (NPT) to explore implementation of the maternal perinatal death surveillance and response (MPDSR) policy in Uganda: a reflection

BackgroundThe implementation of the maternal perinatal death surveillance and response (MPDSR) policy is among the envisaged strategies to reduce the high global burden of maternal and perinatal mortality and morbidity. However, implementation of this policy across various contexts is inconsistent. Theoretically informed approaches to process evaluation can support assessment the implementation of policy interventions such as MPDSR, particularly in understanding what the actors involved actually do. In this article, we reflect on how the normalisation process theory (NPT) was used to explore implementation of the MPDSR policy in Uganda. NPT is a sociological theory concerned with the social organisation of the work (implementation) of making practices routine elements of everyday life (embedding) and of sustaining embedded practices in their social contexts (integration).MethodsThis qualitative multiple case study conducted across eight districts in Uganda and among 10 health facilities (cases) representing four out of the seven levels of the Uganda health care system. NPT was utilised in several ways including informing the study design, structuring the data collection tools (semi-structured interview guides), providing an organising framework for analysis, interpreting and reporting of study findings as well as making recommendations. Study participants were purposely selected to reflect the range of actors involved in the policy implementation process. This included direct care providers located at each of the cases, the Ministry of Health and from agencies and professional associations. Data were collected using semi-structured, in-depth interviews and were inductively and deductively analysed using NPT constructs and subconstructs.Results and conclusionNPT served useful for process evaluation, particularly in identifying factors that contribute to variations in policy implementation. Considering the NPT focus on the agency of people involved in implementation, additional efforts are required to understand how recipients of the policy intervention influence how the intervention becomes embedded within the various contexts.

Therapists' experiences of negative effects in intensive short-term dynamic psychotherapy: A qualitative interview study.

Negative effects of psychotherapy are a broad term that encompasses events such as non-response, deterioration, and novel symptoms. The aim of the present study was to explore experiences with negative effects among clinicians working within an intensive short-term dynamic psychotherapy (ISTDP) framework. Eight ISTDP clinicians consented to participate and were interviewed using semi-structured video interviews. Data were transcribed and analyzed using a reflexive thematic analysis framework. The thematic analysis resulted in five themes. Overall, the clinicians found it difficult to define negative effects, but that negative effects, regardless of cause, could be used therapeutically. Inaccurate assessment was seen as the main cause of negative effects. Other themes concerned the connection between dropout and negative effects, patient feedback, and the ISTDP community's relationship to negative effects. The results are largely in line with qualitative studies of CBT clinicians' views of negative effects although clinicians in the present study emphasized more strongly the therapeutic potential of these events. The research field could be further improved by using mixed-method designs while including both patients and therapists.

Quantitative attribution of industrial agglomeration patterns in Africa: global, local drivers and indirect effects

ABSTRACT Finding appropriate measures to drive industrial agglomeration is particularly urgent for Africa, which has been facing a decline in industrial production activities. Therefore, this study contributed by developing a multi-level spatial analysis framework that explored the global driving mechanisms and local heterogeneity of industrial agglomeration in Africa through various critical factors. The findings are as follows: (1) From 2009 to 2019, the industry in Africa has always been highly concentrated in a few countries, but the degree of agglomeration has been declining, with some countries in the East and West African regions showing a significant increase in the level of industrial agglomeration and a high potential for development. (2) Industrial agglomeration in African countries was driven by several factors, of which GDP per capita, highway network density, and electricity supply were the strongest and most consistent drivers. The impact strength of factors varied considerably across regions. (3) The drivers didn’t act independently and directly on the dependent variable, but were the product of synergy after the interaction between the two factors. Synergies between access to electricity and GDP per capita and other factors dominated the pattern of industrial agglomeration in Africa.

КОНЦЕПТУАЛЬНІ ЗАСАДИ ФОРМУВАННЯ ІНКЛЮЗИВНОГО РИНКУ ПРАЦІ В УКРАЇНІ

Introduction. In the conditions of war, Ukraine faces numerous challenges that affect the socio-economic situation and the functioning of the labor market. At the same time, the formation of an inclusive labor market, which is able to provide equal opportunities for all citizens, including vulnerable groups of the population, which will contribute to social cohesion and economic stability of the country, becomes particularly relevant. This requires the formation of conceptual approaches to the creation of an inclusive labor market in Ukraine, taking into account the peculiarities of wartime and the challenges facing the country. The purpose of the article. The purpose of the study is to determine the conceptual foundations of the formation of an inclusive labor market in Ukraine in wartime conditions based on the identification of the main challenges for attracting vulnerable population groups to the labor market and the development of ways to overcome them in order to ensure the social and economic stability of the state. Methods. The research methodology is based on a comprehensive approach, which includes the analysis of scientific literature, regulatory and legal framework and statistical data. The research uses methods of comparative analysis to determine barriers in the labor market, a systematic approach to determine the conceptual foundations of inclusiveness, and a method of logical generalization to determine practical ways to solve the identified problems. Results. The article identifies the need for the formation of an inclusive labor market in Ukraine in the conditions of war, when socio-economic instability affects access to employment for various population groups. The main barriers to the participation of vulnerable population groups in the labor market, including veterans, internally displaced persons, people with disabilities, youth and women, have been identified. The analysis of the modern legal framework showed that there is currently a shortage of state support tools for their employment. The importance of cooperation between the state, business and the public sector to create equal employment opportunities has been proven. Conceptual approaches to the formation of an inclusive labor market are defined: implementation of professional retraining programs, development of social entrepreneurship and adaptation of workplaces. The need for the formation of a state policy aimed at ensuring equal access to the labor market for all population groups and strengthening the economic stability of Ukraine has been proven. Conclusions. The importance of the formation of an inclusive labor market in Ukraine as a key element of socio-economic stability in the conditions of war has been proven. The proposed conceptual principles ensure the expansion of opportunities for vulnerable population groups, the reduction of unemployment and the increase of social cohesion.

A Comprehensive Exploration of Hellwig’s Taxonomic Measure of Development and Its Modifications—A Systematic Review of Algorithms and Applications

This paper presents an original and comprehensive investigation into the Taxonomic Measure of Development (TMD), introduced by Hellwig in 1968, enriching both its theoretical foundations and practical applications. It provides an overview of various variants of the Hellwig method, including their extensions and applications, while also exploring recent trends across multiple research domains. Primarily developed as a method for multidimensional analysis, TMD has evolved into a pivotal tool in multi-criteria decision-making. It is widely used for evaluating and ranking alternatives, particularly in the analysis of complex socio-economic phenomena and decision-making scenarios involving multiple criteria. This study systematically reviews the original algorithm and its subsequent extensions and modifications, including adaptations for fuzzy sets, intuitionistic fuzzy sets, and interval-valued fuzzy sets. Furthermore, it explores an integrated multi-criteria approach based on Hellwig’s method and its practical applications across various domains. This paper introduces an original approach by conducting a detailed, step-by-step analysis of the TMD framework. This process-oriented analysis is a novel contribution that sets this study apart from typical reviews based on statistical or bibliometric data. By examining key steps in the TMD framework—such as data collection, criterion weighting, data normalization, ideal value determination, distance calculation, and normalization factor—this paper highlights the method’s versatility in addressing complex, real-world decision-making problems. Although similar to the widely used Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method in its reliance on distance to evaluate alternatives, Hellwig’s approach is unique in focusing exclusively on proximity to an ideal solution, without considering distance from a negative ideal. This distinctive emphasis has led to numerous adaptations and extensions that address specific issues such as criterion dependencies, uncertainty, and rank reversal. The findings underscore the continued relevance of the Hellwig method, its recent extensions, and its growing international recognition.

Benchmark dose modeling for epidemiological dose-response assessment using case-control studies.

Following a previous article that focused on integrating epidemiological data from prospective cohort studies into toxicological risk assessment, this paper shifts the focus to case-control studies. Specifically, it utilizes the odds ratio (OR) as the main epidemiological measure, aligning it with the benchmark dose (BMD) methodology as the standard dose-response modeling approach to determine chemical toxicity values for regulatory risk assessment. A standardized BMD analysis framework has been established for toxicological data, including input data requirements, dose-response models, definitions of benchmark response, and consideration of model uncertainty. This framework has been enhanced by recent methods capable of handling both cohort and case-control studies using summary data that have been adjusted for confounders. The present study aims to investigate and compare the "effective count" based BMD modeling approach, merged with an algorithm used for converting odds ratio to relative risk in cohort studies with partial data information (i.e., the Wang algorithm), with the adjusted OR-based BMD analysis approach. The goal is to develop an adequate BMD modeling framework that can be generalized for analyzing published case-control study data. As in the previous study, these methods were applied to a database examining the association between bladder and lung cancer and inorganic arsenic exposure. The results indicate that estimated BMDs and BMDLs are relatively consistent across both methods. However, modeling adjusted OR values as continuous data for BMD estimation aligns better with established practices in toxicological BMD analysis, making it a more generalizable approach.

Framework for Analysis of Queueing Systems with Correlated Arrival Processes and Simultaneous Service of a Restricted Number of Customers in Scenarios with an Infinite Buffer and Retrials

In this paper, we create a framework for the uniform algorithmic analysis of queueing systems with the Markov arrival process and the simultaneous service of a restricted number of customers, described by a multidimensional Markov chain. This chain behaves as the finite-state quasi-death process between successive service-beginning epochs, with jumps occurring at these epochs. Such a description of the service process generalizes many known mechanisms of restricted resource sharing and is well suited for describing various future mechanisms. Scenarios involving customers who cannot enter service upon arrival, access via waiting in an infinite buffer, and access via retrials are considered. We compare the generators of the multidimensional Markov chains describing the operation of queueing systems with a buffer and with retrials and show that the sufficient conditions for the ergodicity of these systems coincide. The computation of the stationary distributions of these chains is briefly discussed. The results can be used for performance evaluation and capacity planning of various queueing models with the Markov arrival process and a variety of different service mechanisms that provide simultaneous service to many customers.

Determinants of Public Participation in Watershed Management in Southeast China: An Application of the Institutional Analysis and Development Framework

Increasingly, adaptive processes and decentralization are vital aspects of watershed governance. Equitable and sustainable water governance requires an understanding that different societal members have unique relationships with the environment and varying levels of interaction with policymakers. However, the factors facilitating public involvement under centralized governance remain less understood. This study combined the Institutional Analysis and Development framework with ordered probit regression to empirically investigate the determinants of willingness to participate (WTP) and actual participation of the public in integrated watershed management (IWM). Data from 933 valid questionnaires collected across 36 counties in Fujian, China, were used to define stakeholders’ perceptions of IWM. Results show that stakeholders are predominantly willing to participate in watershed conservation, management, or planning (85.9%), while only 32.8% frequently attend related events. Pro-environmental intentions were mainly shaped by interactional capacity—information exposure, interpersonal exchanges, and cross-reach support recognition—while actual participation was influenced by perceived biophysical conditions, rules-in-use, socioeconomic factors, and interactional capacity. Frequent observations of poor forest management practices were correlated with higher behavioral intentions, and socioeconomic dynamics significantly affected self-reported actual participation. Information sharing had the most substantial positive impact on both WTP and actual participation. These findings reinforce the necessity for an integrated and holistic approach to regional watershed resource management that fosters inclusivity and sustainability. This study provides workable insights into the social and institutional factors that shape public participation in watershed governance as it evolves toward decentralization.

Communicating life-saving knowledge: The multimodal arrangement in Lifesaver VR

VR applications for medical simulations such as emergency situations offer new ways of providing knowledge and practical skills for saving a life and potentially represent a complex communicative environment. The communicative situations constructed by this environment bring with them an increasing level of interactivity and ergodicity and it is particularly challenging to address these analytically. We address this challenge by looking at Lifesaver VR and providing a foundational framework for the multimodal analysis of the communicative situations created in this application. We describe how information and content units of the game can be built and how these units can then be combined into complex discourse structures outlining the complexity and simultaneity of narrative, instructional, and interactive aspects of the game.

Mapping the evolution of PET/MR research: a bibliometric analysis of publication trends, leading contributors, and conceptual frameworks (2011–2023)

BackgroundPositron emission tomography-magnetic resonance imaging (PET/MR) is a cutting-edge hybrid imaging technology with the potential to revolutionize medical diagnosis. This bibliometric study aims to map the research landscape of PET/MR by analyzing a curated set of Web of Science Core Collection documents from 2011 to 2023.MethodsWe conducted a bibliometric analysis to map the research landscape of PET/MR, leveraging a curated dataset of 3,600 documents retrieved from the Web of Science Core Collection spanning the period from 2011 to 2023. We employed quantitative methods to assess the quantity and distribution of PET/MR studies, including patterns of change, research status, and directions. Additionally, we utilized VOSviewer software to conduct keyword co-occurrence analysis, explore collaborative networks among authors and institutions, and identify influential journals in the field.ResultsResults: The analysis reveals several key insights: (1) a significant increase in the number of PET/MR publications over the past 12 years, highlighting the growing interest and activity in this field; (2) the United States and Germany as the leading countries in terms of research output and collaboration, with a growing presence of other countries such as China; (3) the Journal of Nuclear Medicine and the European Journal of Nuclear Medicine and Molecular Imaging as the most influential journals in the field; (4) a shift in research focus from imaging techniques to clinical applications, with an increasing emphasis on prostate cancer, PSMA, and FDG imaging.ConclusionsThis study provides a comprehensive overview of PET/MR research, identifying prominent trends, key researchers, and influential works. Based on these findings, we propose recommendations for future research directions in this rapidly evolving field.

Incorporating external controls in the design of randomized clinical trials: a case study in solid tumors

BackgroundThe use of historical external control data in clinical trials has grown in interest and needs when considering the design of future trials. Hybrid control designs can be more efficient to achieve the same power with fewer patients and limited resources. The literature is sparse on appropriate statistical methods which can account for the differences between historical external controls and the control patients in a study. In this article, we illustrate the analysis framework of a clinical trial if a hybrid control design was used after determining an RCT may not be feasible.MethodsWe utilize two previously completed RCTs in nonsquamous NSCLC and a nationwide electronic health record derived de-identified database as examples and compare 5 analysis methods on each trial, as well as a set of simulations to determine operating characteristics of such designs.ResultsIn single trial estimation, the Case Weighted Adaptive Power Prior provided estimated treatment hazard ratios consistent with the original trial’s conclusions with narrower confidence intervals. The simulation studies showed that the Case Weighted Adaptive Power Prior achieved the highest power (and well controlled type-1 error) across all 5 methods with consistent study sample size.ConclusionsBy following the proposed hybrid control framework, one can design a hybrid control trial transparently and accounting for differences between control groups while controlling type-1 error and still achieving efficiency gains from the additional contribution from external controls.